Happy to see that DeMask built with asteroid won the first place of the @PyTorch summer #hackathon!
The model allows you to enhance muffled speech when wearing facemask
Demo: https://t.co/mGxGbkvLGM
👋 to our team: @mnlpariente@michelolzam @_jonashaag and Samuel Cornell
DJs making music magic, create yours with AudioShake stems. djay Pro from @algoriddim now includes AudioShake’s tech to isolate vocals, instruments, and drums at the highest quality available to the industry. On mobile. 🎧📷#djtools#beatmaking
Our paper on lyrics transcription evaluation is on arXiv with updated and extended results (including Whisper v3)!
📄 https://t.co/6BTw0UoLl1
Also, the benchmark is now on @paperswithcode:
🏆 https://t.co/xaky6qz8Ya
👏 @faroit@h_schreiber@Luke_Miner@cnst_ant@AudioShakeAI
We just released Jam-ALT, a formatting- and punctuation-aware automatic lyrics transcription benchmark (based on the JamendoLyrics dataset) that follows music industry guidelines. 🧵
🔎 https://t.co/uTZDfjLFs5
🤗 https://t.co/kGmyaC0XFu
🧑💻 https://t.co/D4lxzwU8qN
@zhaojw1998 same here for us. Very unfortunate and not really fair as it can't be automated. Why not let more papers to be submitted and review them by quality instead of submission time?
I am looking for reviewers for a @JOSS_TheOJ submission with expertise in speech and python. The software under review is a new speech enhancement module of https://t.co/nBJ8wUk25C (hence its so difficult to get reviewers without conflicts of interest). Any pointer is helpful!
Join us for a special edition of our Mila Music + AI Reading Group from February 8th to 22nd!
We're excited to host 5 teams from the 2022 AI Song Contest, an international contest where musicians and scientists collaborate to explore human-ai co-creativity.
#Pytorch implementation of MusicLM, new SOTA model for music generation using attention networks plus embeddings from MuLan, a text-audio contrastive learned model https://t.co/pA98ZJ61iM
🎻 The SDX23 challenge introduces a new formulation of audio source separation: cinematic sound separation.
The task is to separate a movie's audio into three tracks: dialogue, sound effects & music.
📕 Give it a try using the starter kit.
https://t.co/51A8ODkv3K
#AudioLDM, the text-to-audio model, is now available on HuggingFace and GitHub to play with!
We will add more functionality and further improve the model performance in the near future.
Share the interesting samples you generate!
https://t.co/cwHsJ34eZb
https://t.co/fKQ9Q8LF5P
@naotokui_en@csteinmetz1 Training is just a very small aspect of it. Lawyers will first go after the obvious things: the startups that can generate new Taylor Swift songs.
Hey music separation researchers. We added a new definition of the SDR metric when we launched the last @sounddemix. To make it less confusing for future papers, we want to rename the metric. Please vote
@JonathanLeRoux@ethanmanilow For the challenge we run mean across songs. But many papers and also (rightfully) show median across songs as outliers can be dramatic.